Wednesday, February 22, 2012

When analyzing complex systems, applied mathematicians often
turn to Monte Carlo simulations. The concept is straightforward. Change the
state of the system by making a random move. If the new state is an
improvement, make a new random move in a direction suggested by extrapolation.
Otherwise, make a random move in a different direction. Repeat until a certain
variable is optimized.

A commodity market is a real-life concurrent Monte Carlo
system. Market participants make sequences of moves. Each new move is random,
though it incorporates experience gained from previous moves. The resulting
system is a remarkably effective mechanism to produce commodities at the lowest
possible cost while adjusting to changing market conditions. Adam Smith called
it the invisible hand of the free market.

In severely disrupted markets, the invisible hand may take
an unacceptably long time, because Monte Carlo systems may remain stuck in
local minima. We may understand this point by visualizing a mountain range with
many peaks and valleys. An observer inside one particular valley thinks the
lowest point is somewhere on that valley’s floor. He is unaware of other
valleys at lower altitudes. To see these, he must climb to the rim of the
valley, far away from the observed local minimum. This takes a very long time with
small random steps that are biased in favor of going towards the observed local
minimum.

For this reason, Monte Carlo simulations use strategies that
incorporate large random moves. One such strategy, Simulated Annealing, is
inspired by a metallurgical technique that improves the crystallographic
structure of metals. During the annealing process, the metal is heated and
cooled in a controlled fashion. The heat provides energy to change large-scale crystal
structures in the metal. As the metal cools, restructuring occurs only at gradually
smaller scales. In Simulated Annealing, the simulation is run “hot” when large
random moves are used to optimize the system at coarse granularity. When sufficiently
near a global minimum, the system is “cooled“, and smaller moves are used for
precision at fine granularity. Note that, from a Monte Carlo perspective, large
moves are just as random as small moves. Each individual move may succeed or
fail. What matters is the strategy that guides the sequence of moves.

When major market disruptions occur, resistance to change
breaks down and large moves become possible. (The market to runs “hot” in the
Simulated Annealing sense.) Sometimes, government leaders or tycoons of
industry initiate large moves, because they believe, right or wrong, that they
can take the market to a new global minimum. Politicians enact new laws, or they
orchestrate bailouts. Tycoons make large bets that are risky by conventional measures.
Sometimes, unforeseen circumstances force markets into making large moves.

The music industry experienced such an event in late 1999,
when Napster, the illegal music-sharing site, suddenly became popular.
Eventually, this disruption enabled then-revolutionary business models like
iTunes, which could compete with illegal downloading. This stopped the
hemorrhaging, though not without leaving a disastrous trail. Traditional music
retailers, distributors, and other middlemen were forced out. Revenue streams
never recovered. With the Stop Online Piracy Act (SOPA), the music industry, joined
by the entertainment industry, was trying to undo some of the damage. If
enacted, it would have caused significant collateral damage, but it would have
done nothing to reduce piracy. This is covered widely in the blogosphere. For
example, consider blog posts by Eric Hellman [1][2] and David Post [3].

While SOPA is dead, other attempts at antipiracy legislation
are in the works. Some may succeed legislatively and may be enacted. In the
end, however, heavy-handed legislation will fail. The evolution towards ubiquitous
information availability (pirated or not) is irreversible. Even the cruelest of
dictators cannot contain the flow of information. Why would anyone think
democracies could? Eventually, laws follow society’s major trends. They always
do.

When Napster became popular, the music industry was unable
to fight back, because its existing distribution channels had become technologically
obsolete. Napster was the large random move that made visible a new valley at lower
altitude. Without Napster, some other event, circumstance, or product would eventually
have come along, caused havoc, and be blamed. Antipiracy legislation might have
delayed the music industry’s problems in 1999, but it will not solve the entertainment
industry’s problems in 2012.

In the new market, piracy may no longer be the problem it
once was. Consumers are willing to pay for convenience, quality of service, and
security (absence of malware). Piracy may still depress revenues, but there are
at least three other reasons for declining revenues. (1) Revenues no longer support
many middlemen, and this is reflected in lower music prices through free-market
competition. (2) Some consumers are interested in discovering new artists themselves,
not in listening to artists discovered on their behalf by record labels. (3)
The recession has reduced discretionary income.

It is difficult to assess the relative importance of
disintermediation, behavior change, recession, and piracy. But the effect of
piracy on legal downloads is probably much less than thought. This may be good
news for the music industry. After many large and disruptive moves, the music
market may be near a new global minimum. Here, it can rebuild and find new
profit-making ventures. These are the kind of conventional “small” moves for a normal,
non-disrupted market.

About Me

Eric is a technology consultant specializing in the strategic application of new technologies in academic computing and library services.

Prior to this, Eric was the Director of Library Information Technology, a Senior Research Associate and Lecturer in Applied Mathematics at the California Institute of Technology. Eric holds a computer science degree from the K. U. Leuven (Belgium) and a Ph. D. in Mathematics from the Courant Institute, New York University, NY. He is the author of papers in scientific computing, library technology, and the graduate textbook "Concurrent Scientific Computing", published by Springer-Verlag.

He chaired the OpenURL standardization committee, which developed the OpenURL ANSI standard. He is on the Board of Directors of the Networked Digital Library of Theses and Dissertations (NDLTD).